An approach to identify miRNA associated with cancer altered pathways

Giovanna Maria Ventola, Antonio Colaprico, Fulvio D'Angelo, Vittorio Colantuoni, Giuseppe Viglietto, Luigi Cerulo, Michele Ceccarelli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

MicroRNAs play an important role in the regulation of gene expression by binding mRNA targets causing their degradation or blocking their translation. Several genes has been found to be implicated as miRNA targets in different types of malignant tumors suggesting their involvement in cancer pathogenesis. Detecting direct miRNA-targets associations is not straightforward as in principle targets expressions are not altered except when they are completely repressed by the degradation complex. In this paper we propose an approach to identify direct miRNA-targets associations hypotheses by means of indirect association measures such as mutual information. Indirect regulons of miRNA and Transcription Factors (TFs) are compared with the Fisher's exact test to identify potential co-regulations which may constitute potential miRNA-TF direct associations. We apply the method on two cancer datasets, Colon and Lung, drawn from the Cancer Genome Atlas (TGCA) obtaining promising results.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages399-408
Number of pages10
Volume8158 LNCS
DOIs
Publication statusPublished - 11 Nov 2013
Externally publishedYes
Event17th International Conference on Image Analysis and Processing, ICIAP 2013 - Naples, Italy
Duration: 9 Sep 201313 Sep 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8158 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other17th International Conference on Image Analysis and Processing, ICIAP 2013
CountryItaly
CityNaples
Period9/9/1313/9/13

Fingerprint

MicroRNA
Transcription factors
Pathway
Cancer
Genes
Degradation
Target
Gene expression
Tumors
Association reactions
Transcription Factor
Association Measure
Fisher's Exact Test
Atlas
Lung
Mutual Information
Messenger RNA
Gene Expression
Tumor
Genome

Keywords

  • gene regulatory networks
  • miRNA
  • reverse engineering

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Ventola, G. M., Colaprico, A., D'Angelo, F., Colantuoni, V., Viglietto, G., Cerulo, L., & Ceccarelli, M. (2013). An approach to identify miRNA associated with cancer altered pathways. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8158 LNCS, pp. 399-408). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8158 LNCS). https://doi.org/10.1007/978-3-642-41190-8_43

An approach to identify miRNA associated with cancer altered pathways. / Ventola, Giovanna Maria; Colaprico, Antonio; D'Angelo, Fulvio; Colantuoni, Vittorio; Viglietto, Giuseppe; Cerulo, Luigi; Ceccarelli, Michele.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8158 LNCS 2013. p. 399-408 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8158 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ventola, GM, Colaprico, A, D'Angelo, F, Colantuoni, V, Viglietto, G, Cerulo, L & Ceccarelli, M 2013, An approach to identify miRNA associated with cancer altered pathways. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 8158 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8158 LNCS, pp. 399-408, 17th International Conference on Image Analysis and Processing, ICIAP 2013, Naples, Italy, 9/9/13. https://doi.org/10.1007/978-3-642-41190-8_43
Ventola GM, Colaprico A, D'Angelo F, Colantuoni V, Viglietto G, Cerulo L et al. An approach to identify miRNA associated with cancer altered pathways. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8158 LNCS. 2013. p. 399-408. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-41190-8_43
Ventola, Giovanna Maria ; Colaprico, Antonio ; D'Angelo, Fulvio ; Colantuoni, Vittorio ; Viglietto, Giuseppe ; Cerulo, Luigi ; Ceccarelli, Michele. / An approach to identify miRNA associated with cancer altered pathways. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8158 LNCS 2013. pp. 399-408 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{748db9dfb0834657aee67881b0d96ac0,
title = "An approach to identify miRNA associated with cancer altered pathways",
abstract = "MicroRNAs play an important role in the regulation of gene expression by binding mRNA targets causing their degradation or blocking their translation. Several genes has been found to be implicated as miRNA targets in different types of malignant tumors suggesting their involvement in cancer pathogenesis. Detecting direct miRNA-targets associations is not straightforward as in principle targets expressions are not altered except when they are completely repressed by the degradation complex. In this paper we propose an approach to identify direct miRNA-targets associations hypotheses by means of indirect association measures such as mutual information. Indirect regulons of miRNA and Transcription Factors (TFs) are compared with the Fisher's exact test to identify potential co-regulations which may constitute potential miRNA-TF direct associations. We apply the method on two cancer datasets, Colon and Lung, drawn from the Cancer Genome Atlas (TGCA) obtaining promising results.",
keywords = "gene regulatory networks, miRNA, reverse engineering",
author = "Ventola, {Giovanna Maria} and Antonio Colaprico and Fulvio D'Angelo and Vittorio Colantuoni and Giuseppe Viglietto and Luigi Cerulo and Michele Ceccarelli",
year = "2013",
month = "11",
day = "11",
doi = "10.1007/978-3-642-41190-8_43",
language = "English",
isbn = "9783642411892",
volume = "8158 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "399--408",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - An approach to identify miRNA associated with cancer altered pathways

AU - Ventola, Giovanna Maria

AU - Colaprico, Antonio

AU - D'Angelo, Fulvio

AU - Colantuoni, Vittorio

AU - Viglietto, Giuseppe

AU - Cerulo, Luigi

AU - Ceccarelli, Michele

PY - 2013/11/11

Y1 - 2013/11/11

N2 - MicroRNAs play an important role in the regulation of gene expression by binding mRNA targets causing their degradation or blocking their translation. Several genes has been found to be implicated as miRNA targets in different types of malignant tumors suggesting their involvement in cancer pathogenesis. Detecting direct miRNA-targets associations is not straightforward as in principle targets expressions are not altered except when they are completely repressed by the degradation complex. In this paper we propose an approach to identify direct miRNA-targets associations hypotheses by means of indirect association measures such as mutual information. Indirect regulons of miRNA and Transcription Factors (TFs) are compared with the Fisher's exact test to identify potential co-regulations which may constitute potential miRNA-TF direct associations. We apply the method on two cancer datasets, Colon and Lung, drawn from the Cancer Genome Atlas (TGCA) obtaining promising results.

AB - MicroRNAs play an important role in the regulation of gene expression by binding mRNA targets causing their degradation or blocking their translation. Several genes has been found to be implicated as miRNA targets in different types of malignant tumors suggesting their involvement in cancer pathogenesis. Detecting direct miRNA-targets associations is not straightforward as in principle targets expressions are not altered except when they are completely repressed by the degradation complex. In this paper we propose an approach to identify direct miRNA-targets associations hypotheses by means of indirect association measures such as mutual information. Indirect regulons of miRNA and Transcription Factors (TFs) are compared with the Fisher's exact test to identify potential co-regulations which may constitute potential miRNA-TF direct associations. We apply the method on two cancer datasets, Colon and Lung, drawn from the Cancer Genome Atlas (TGCA) obtaining promising results.

KW - gene regulatory networks

KW - miRNA

KW - reverse engineering

UR - http://www.scopus.com/inward/record.url?scp=84887118201&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84887118201&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-41190-8_43

DO - 10.1007/978-3-642-41190-8_43

M3 - Conference contribution

SN - 9783642411892

VL - 8158 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 399

EP - 408

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -